This research, which identifies landscapes and panoramic views painted by Da Vinci in La Gioconda (Mona Lisa), uses both quantitative and comparative methods including digital terrain models, geomorphological mapping, image analysis, and detailed study of historical documents. The methods and research are an extension of a highly successful project to document the landscapes in the paintings of Piero della Francesca. The precise representation of Renaissance landscapes is important not only for cultural and historical studies, but also permits a comparison of forms of features with the present day, a type of repeat photography database that has already suggested strong hydrological contrasts. The landscapes of La Gioconda and Madonna Litta center in the high Val Marecchia area (Central Italy). The identification of these landscapes permits and enables a new dimension in cultural, historical, and geomorphological studies.

The Da Vinci Landscape Code; Exploring the Panorama behind La Gioconda

NESCI, OLIVIA;
2013

Abstract

This research, which identifies landscapes and panoramic views painted by Da Vinci in La Gioconda (Mona Lisa), uses both quantitative and comparative methods including digital terrain models, geomorphological mapping, image analysis, and detailed study of historical documents. The methods and research are an extension of a highly successful project to document the landscapes in the paintings of Piero della Francesca. The precise representation of Renaissance landscapes is important not only for cultural and historical studies, but also permits a comparison of forms of features with the present day, a type of repeat photography database that has already suggested strong hydrological contrasts. The landscapes of La Gioconda and Madonna Litta center in the high Val Marecchia area (Central Italy). The identification of these landscapes permits and enables a new dimension in cultural, historical, and geomorphological studies.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2608838
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